Humans vary in their genetic susceptibility to the toxic effects of chemicals found at Superfund sites.[unreadable] Cancers and other forms of toxicity may arise from adverse gene-environment interactions. Genetic[unreadable] susceptibility to the toxic effects of a chemical is likely to be related to the cellular targets of the chemical[unreadable] and its metabolites. However, we still have a limited understanding of cellular targets for many of the[unreadable] priority chemicals on the Superfund list. We will take advantage of the conservation of basic metabolic[unreadable] pathways and fundamental cellular processes between the yeast S. cerevisiae and humans to identify[unreadable] candidate human susceptibility genes. Here, we propose a new approach to discover these targets in yeast[unreadable] and human cells using parallel deletion analysis (PDA) and RNA interference (RNAi), respectively. Deletion[unreadable] strains for almost every yeast gene enable new approaches to determine in parallel (PDA) the relative[unreadable] importance of each yeast gene for susceptibility (sensitivity) to a chemical toxicant. We propose to identify[unreadable] candidate susceptibility genes for selected priority Superfund chemicals that require metabolic activation[unreadable] including benzene, polycyclic aromatic hydrocarbons (PAHs), halogenated aliphatic hydrocarbons, and for[unreadable] selected metals such as arsenic and cadmium, which do not. We will select and prioritize likely human[unreadable] candidate genes by computational analysis of the yeast data sets. The candidate human susceptibility[unreadable] genes will be silenced in appropriate human cell lines using RNAi so that their roles in sensitivity to[unreadable] cytotoxicity, genotoxicity and epigenetic effects of the Superfund chemical and/or its metabolites can be[unreadable] evaluated. We suggest that this approach will identify genes that confer human susceptibility to Superfund[unreadable] chemicals and their metabolites and will enable future work to examine associations between variants in[unreadable] these genes and adverse outcomes. In addition, this work will likely provide important insights in the[unreadable] cellular processes leading to toxicity for priority Superfund chemicals.